{"id":"https://openalex.org/W3119687918","doi":"https://doi.org/10.1109/access.2021.3051646","title":"Blind System Identification in Noise Using a Dynamic-Based Estimator","display_name":"Blind System Identification in Noise Using a Dynamic-Based Estimator","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3119687918","doi":"https://doi.org/10.1109/access.2021.3051646","mag":"3119687918"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3051646","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051646","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09323054.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09323054.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012463337","display_name":"Sumona Mukhopadhyay","orcid":"https://orcid.org/0000-0001-9583-1867"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sumona Mukhopadhyay","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0001-9583-1867","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763026","display_name":"Boyuan Li","orcid":"https://orcid.org/0000-0003-2899-8848"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Boyuan Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2899-8848","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061884304","display_name":"Henry Leung","orcid":"https://orcid.org/0000-0002-5984-107X"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Henry Leung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5984-107X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7721,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69197295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"12861","last_page":"12878"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10244","display_name":"Chaos control and synchronization","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.8241223096847534},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6843264698982239},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5957089066505432},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.590483546257019},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5082494616508484},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.47297540307044983},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.468517541885376},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.44171205163002014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.438279390335083},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4346056580543518},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42908474802970886},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.42771580815315247},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.4150713384151459},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.3935942053794861},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2920302748680115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2403842806816101},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.10456505417823792},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.09094980359077454}],"concepts":[{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.8241223096847534},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6843264698982239},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5957089066505432},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.590483546257019},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5082494616508484},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.47297540307044983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.468517541885376},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.44171205163002014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.438279390335083},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4346056580543518},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42908474802970886},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.42771580815315247},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.4150713384151459},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3935942053794861},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2920302748680115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2403842806816101},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.10456505417823792},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.09094980359077454},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3051646","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051646","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09323054.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:becafac061194e5bae6de2cf64c94d63","is_oa":true,"landing_page_url":"https://doaj.org/article/becafac061194e5bae6de2cf64c94d63","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 12861-12878 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3051646","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051646","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09323054.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3119687918.pdf","grobid_xml":"https://content.openalex.org/works/W3119687918.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W582202242","https://openalex.org/W1487453520","https://openalex.org/W1549386224","https://openalex.org/W1615382792","https://openalex.org/W1975492453","https://openalex.org/W1976491864","https://openalex.org/W1981994692","https://openalex.org/W1990416710","https://openalex.org/W2002131976","https://openalex.org/W2011203427","https://openalex.org/W2011547255","https://openalex.org/W2013460452","https://openalex.org/W2018036872","https://openalex.org/W2018869829","https://openalex.org/W2019791172","https://openalex.org/W2022882941","https://openalex.org/W2024162248","https://openalex.org/W2038623285","https://openalex.org/W2041557696","https://openalex.org/W2044835875","https://openalex.org/W2065822605","https://openalex.org/W2079332753","https://openalex.org/W2097754770","https://openalex.org/W2106297417","https://openalex.org/W2113486168","https://openalex.org/W2115339608","https://openalex.org/W2115723730","https://openalex.org/W2135818760","https://openalex.org/W2138536663","https://openalex.org/W2140126209","https://openalex.org/W2141514928","https://openalex.org/W2148087508","https://openalex.org/W2148812503","https://openalex.org/W2154331663","https://openalex.org/W2154584980","https://openalex.org/W2155045574","https://openalex.org/W2157169955","https://openalex.org/W2158038039","https://openalex.org/W2161638456","https://openalex.org/W2168716384","https://openalex.org/W2398714011","https://openalex.org/W2483388146","https://openalex.org/W2588611571","https://openalex.org/W2787043370","https://openalex.org/W2799712149","https://openalex.org/W2890573290","https://openalex.org/W2984985558","https://openalex.org/W2989217263","https://openalex.org/W3021284771","https://openalex.org/W3030890607","https://openalex.org/W3094402815","https://openalex.org/W3124661333","https://openalex.org/W6629002598","https://openalex.org/W6682785043","https://openalex.org/W6683389101"],"related_works":["https://openalex.org/W2585557503","https://openalex.org/W2169354510","https://openalex.org/W1967296369","https://openalex.org/W4389474210","https://openalex.org/W1971427935","https://openalex.org/W2014635939","https://openalex.org/W4299934179","https://openalex.org/W2073381184","https://openalex.org/W1909999440","https://openalex.org/W1576040274"],"abstract_inverted_index":{"In":[0],"this":[1],"work":[2],"we":[3],"consider":[4],"the":[5,34,49,61,75,86,91,105,113,143,187,191],"problem":[6],"of":[7,44,56,74,90,115,119,156,202],"blind":[8,116,134,164,193],"system":[9,117,144],"identification":[10,118,135,165,194],"in":[11,112],"noise":[12],"driven":[13,146],"by":[14,147],"an":[15,109],"independent":[16],"and":[17,122,151],"identically":[18],"distributed":[19],"(i.i.d)":[20],"non-Gaussian":[21],"signal":[22],"generated":[23],"from":[24],"a":[25,41,179,199],"deterministic":[26],"nonlinear":[27],"chaotic":[28,149],"system.":[29],"A":[30],"new":[31],"estimator":[32,55,77,107],"for":[33],"phase":[35,64],"space":[36,65],"volume":[37,66],"(PSV)":[38],"which":[39],"is":[40,46,58,101,130,145,160,171],"dynamic-based":[42],"property":[43],"chaos":[45],"derived":[47],"using":[48],"maximum":[50,62],"likelihood":[51,63],"formulation.":[52],"This":[53],"novel":[54],"PSV":[57],"denoted":[59],"as":[60,108],"(ML-PSV).":[67],"The":[68,127,154],"Cram\u00e9r":[69],"Rao":[70],"Lower":[71],"Bound":[72],"(CRLB)":[73],"ML-PSV":[76,92,106,188],"has":[78],"also":[79],"been":[80],"derived.":[81],"We":[82],"have":[83],"shown":[84,131],"that":[85,103,186],"mean":[87],"square":[88],"error":[89],"estimate":[93],"gradually":[94],"approaches":[95],"its":[96],"CRLB":[97],"asymptotically.":[98],"An":[99],"algorithm":[100],"formulated":[102],"applies":[104],"objective":[110],"function":[111],"task":[114],"autoregressive":[120],"(AR)":[121],"moving":[123],"average":[124],"(MA)":[125],"models.":[126],"proposed":[128,158],"technique":[129,170],"to":[132],"improve":[133],"performance":[136],"at":[137,198],"low":[138,200],"signal-to-noise":[139],"ratio":[140],"(SNR)":[141],"when":[142],"both":[148],"numeric":[150],"symbolic":[152],"signals.":[153],"efficiency":[155],"our":[157],"method":[159,189],"compared":[161],"with":[162],"conventional":[163],"methods":[166,195],"through":[167,174],"simulations.":[168],"Our":[169],"further":[172],"validated":[173],"experimental":[175],"evaluation":[176],"based":[177],"on":[178],"software":[180],"defined":[181],"radio":[182],"(SDR).":[183],"Results":[184],"show":[185],"outperforms":[190],"existing":[192],"producing":[196],"estimates":[197],"SNR":[201],"<inline-formula":[203],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[204],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[205],"<tex-math":[206],"notation=\"LaTeX\">$\\le20$":[207],"</tex-math></inline-formula>":[208],"dB.":[209]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
